Background: Toria is a widely grown Brassica sp. crop in India due to its rigidity. Production quality and quantity are the biggest obstacles to toria cultivation. Crop productivity is influenced by genes, environment and nutrition. 
&nbsp; 
Methods: In 2021-22 and 2022-23, the experimental farm at Lovely Professional University&rsquo;s School of Agriculture in Jalandhar, Punjab carried this investigation. The experiment adopted a randomized block design (Factorial) with 3 sowing dates and 4 fertilizer levels, replicated 3 times. 
&nbsp; 
Result: D1&nbsp;(1st&nbsp;October) and 100% fertilizer levels had the highest values for siliqua plant-1&nbsp;(189.83), Siliqua length (4.32 cm), seeds (13.83), test weight (4.03 g), seed yield (1191.25 kg ha-1) and harvest index (36.02%), while stover yield (2249.25 kg ha-1) was highest in 2nd&nbsp;DOS (15th&nbsp;October). The 1st&nbsp;DOS and 100% RDF interaction yielded optimal yield, nutrient absorption and concentration values. Thus, 100% RDF should be applied to toria plants on October 1 for better production. 
&nbsp;

Investigating The Influence of Temporal Dynamics and Nutrient Levels on Soil Health, Plant Uptake and Yield Attributes of Toria in the Trans-gangetic Region of Punjab Towards Sustainable Development Goals

Background: In agriculture, Crop Yield Prediction (CYP) by Deep Learning (DL) models such as Deep Neural Network (DNN) and Convolutional Neural Network (CNN) is an emerging technique that utilizes weather, soil and previous year yield information for different crops. On the other hand, these models often struggle to effectively handle time-series data, which can lead to challenges in capturing temporal relationships between weather, soil and crop yield factors. This can affect the accuracy of predicting crop yields. 
 
Methods:&nbsp;To address this issue, the Fixed-Adaptive Temporal Attention Network (FAT-AttNet) is proposed in this study for CYP using a time-series crop yield dataset, which includes historical information on soil, weather and crop yields. A normalization technique is used to preprocess the dataset, removing irregularities and empty values. Next, the FAT-AttNet model is trained to predict crop yields. This model consists of fixed and adaptive temporal modules. In the fixed temporal module, 18 parallel one-dimensional (1D) CNNs are used to process the stable factors, such as soil data, to capture temporal features. In the adaptive temporal module, 16 parallel two-dimensional (2D) CNNs capture the dynamic relationships among weather, soil and crop growth factors over time. The results from these models are combined using the lateral connection and an attention strategy is applied to adjust the weight of each factor for more accurate predictions. Furthermore, a Fully Connected (FC) layer and an output layer are used to predict crop yields. 
 
Result: The experiments are conducted using an agricultural crop yield in Indian States dataset (ACY-ISD) to evaluate the performance of the FAT-AttNet model for five major crops in Tamil Nadu using the historical data from 2002 to 2023.&nbsp; The results show that the FAT-AttNet model achieves a Mean Absolute Error (MAE) of 0.05, 0.059, 0.061, 0.058 and 0.074 for groundnut, maize, moong, rice and urad yield predictions, respectively. &nbsp;The Root Mean Square Error (RMSE) for the groundnut, maize, moong, rice and urad yield predictions is 0.217, 0.268, 0.245, 0.235 and 0.266, respectively. The correlation coefficients for groundnut, maize, moong, rice and urad yield predictions are 0.862, 0.846, 0.864, 0.860 and 0.859, respectively. The results of FAT-AttCNN models outperform the Improved Optimizer Function with Long Short-Term Memory (IOF-LSTM), CNN-Bidirectional LSTM (BiLSTM), MayFly Algorithm empowered attention-BiLSTM (MFA-BiLSTM) and Spatio-Temporal Attention-based CNN (STACNN) models. 
&nbsp;

Fixed-adaptive Temporal Attention Network for Predicting Crop Yield

<div>Background: Land surface temperature (LST) and vegetation play a very significant role in influencing soil moisture and its interaction with the crop. Crop Water Stress Index (CWSI) is one of the most applicable indices to measure the level of water stress to crops that can be quantified using satellite imagery. The upper Brahmaputra river valley of Assam is a rapidly growing region experiencing extensive urban expansion, which necessitates the assessment of changes in spatio-temporal LST and vegetation dynamics for sustainable land management. 
&nbsp; 
Methods: MODIS images were applied in this study to assess spatio-temporal LST, vegetation and Crop Water Stress (CWS). Normalized Difference Vegetation Index (NDVI) was adopted to assess the spatio-temporal vegetation dynamics. A correlation study was conducted to understand the relationship between LST, NDVI and CWSI. 
&nbsp; 
Result: It was observed that there was a strong negative correlation between LST and NDVI, whereas a strong positive correlation was found between LST and CWSI. Hotspot areas characterized by high temperature, low vegetation and high crop water stress were delineated in the ArcGIS platform. Between 2001 and 2021, all LST zones showed an increase in both maximum and minimum temperatures. Contour tilling, mulching and shade nets may effectively enhance soil moisture retention, fertility and microclimatic conditions in these hotspot areas.</div>

Spatio-temporal Assessment of Land Surface Temperature, Vegetation and Crop Water Stress for Sustainable Land Management in Upper Brahmaputra Valley, Assam

<div>Background: The present study aims to study the temporal evolution of the salinity of three profiles of Solonchaks which are in the region of R&eacute;lizane (Algeria). The aim is to determine the temporal changes in salinity between 2010 and 2014, by comparing saline profiles to determine the direction and intensity of variation in soil salinity. 
 
Methods: The experiment was carried out on three soil profiles (Solonchaks) which are located in the perimeter of the Mina which is located in the Bas-Ch&eacute;lif. 
 
Result: The study of the temporal evolution of salinity showed that the majority of horizons underwent desalination between the 2010 and 2014 campaign. This desalination occurred at a speed between 3.67 and 10.74 dS m-1 per year. This would be due to a partial leaching of salts from the surface horizons during the rainy season. The soils studied are marked by a higher salinity during the 2010 compared to the 2014 campaign. The principal component analysis (PCA) reveals that the chemical elements of the soil solution have the most weight on the variability of salinity, and the Wilcoxon test reveals that the difference between the EC of the 2010 campaign and that of 2014 is significant.</div>

Salinity Temporal Evolution Assessment under Mediterranean Conditions

<div>Background: The present study on the topic &ldquo;Phytomorphology and nutrient dynamics of mulberry leaves&rdquo; revealed high variability among mulberry varieties. Internodes were largest in variety Tr4 (6.06%). Actual leaf area was high in variety S146 (275.57 cm2). Numbers of leaves per meter branch was largest in variety S1531 (20.9). During 5 periodic sampling from sprouting to maturity average fresh and dry leaf weight of 100 leaves was high (197.93g) and (60.24g) respectively during 5th sampling. Average moisture content was high (83.41%) during 1st sampling highest average chlorophyll content (SPAD value) was also observed during 4th sampling (40.01%). Acidity was also high in variety Tr4 during maturity. Sugar content was high in variety T1 (3.66%) during 1st sampling (15 days). Starch and ash content was high in variety S1708 (43.06%) and (32.50%) during 5th sampling. Nitrogen and protein content was highest in variety S1608 (5.02%) and (31.56%) respectively during 1st sampling.&nbsp; 
 
Methods: In the field-laboratory investigation was conducted at Division of Sericulture,&nbsp;Division of Biochemistry and Plant Physiology, SKUAST-J, Chatha, during spring 2013. Ten mulberry varieties T1, Tr4, V1, S146, S1708, S799, S1608, S1531, S41 and Sujanpur were evaluated for phytomorphological and nutrient dynamic studies. The experiment was laid in complete randomized block design with three replicates. Each variety was taken as treatment and observations were recorded after 15 days interval upto 75th day after sprouting.&nbsp; 
 
Result: On the basis of current result, parameter observed fluctuations from the date of sprouting till maturity. Varietal response to periodic sampling too varied. Protein decreases age along with sugar, nitrogen. On the contrary starch, biomass, ash, chlorophyll shown a gradual increase. This information can be utilized to harvest a particular type of leaf for a particular age and rearing.</div>

<div>Phytomorphology and Nutrient Dynamics of Mulberry Leaf</div>

<div>Background: Anestrus is one of the most commonly encountered infertility problems in cattle and buffalo in India. Jaffarabadi is one of the heaviest buffalo breeds of the world and is a native of Saurashtra region of Gujarat. The breed is known for poor reproductive efficiency. To improve its reproductive efficiency, this study was undertaken on acyclic Jaffarabadi animals employing double Ovsynch protocol and its assessment through ovarian dynamics and blood biochemical and endocrine profile on a farm.&nbsp; 
 
Methods: The study included acyclic post-pubertal Jaffarabadi heifers (age 42&plusmn;2 and 48&plusmn;2 months; Gr-I and Gr-II, n=6 each) and the postpartum lactating acyclic buffaloes (Gr-III, n=6) using a double Ovsynch protocol, which consisted of i/m injections of 20 &micro;g Buserelin acetate on days 0, 10, 17 and 26 and 500 &micro;g Cloprostenol sodium on days 7 and 24, with a timed insemination on day 27. Ovarian dynamics was monitored by performing ultrasonography using real-time B-mode ultrasound scanner together with blood sampling for hormonal and biochemical profile on each day of hormone therapy and then on days 0, 12, 21 and 35 post-AI. The animals inseminated at induced estrus/FTAI were followed for return to estrus, if any. Pregnancy was confirmed in non-return cases on day 35 by ultrasonography and on day 70 by per rectal examination. The findings on ovarian dynamics, plasma endocrine and biochemical profile were compared statistically between groups and periods and fertility rates between groups. 
 
Result: In animals of treatment group I and II, a significant (p&lt;0.05) increase in numbers of small follicles was observed on day 26. Number of large sized follicles was significantly (p&lt;0.05) higher on day 26 in comparison to day 0 and day 7 in group III animals. Large and subordinate follicular diameters increased gradually, but the differences between periods were significant (p&lt;0.001) only in group III with the highest diameter of large follicle on day 17. Plasma FSH and LH concentrations differed significantly (p&lt;0.001) among groups at all-time intervals. Plasma LH in group I and III differed significantly (p&lt;0.001). Plasma estrogen level was significantly (p&lt;0.05) higher in group II than group III. Plasma progesterone concentrations in group I and II animals were significantly higher on day 35 post-AI. Plasma insulin levels were significantly (p&lt;0.01) lower on all days for group III animals than group I and II. Blood glucose level was significantly (p&lt;0.001) higher in group I on day 17 as compared to group II and III. Plasma total cholesterol was significantly (p&lt;0.05) higher in group III as compared to group I and II. The conception rates at first service/FTAI in double Ovsynch treated animals of group I, II and III were 66.66, 83.33 and 16.66 %, respectively. Thus it was concluded that ovarian structures and the plasma endocrine profile reflected the ovarian response to different hormonal injections and that double Ovsynch protocol could be a better choice for improving conception rate in post-pubertal acyclic Jaffarabadi buffalo heifers as compared to multiparous acyclic buffaloes.</div>

Evaluation of Double Ovsynch Protocol in Acyclic Jaffarabadi Heifers and Buffaloes with Respect to Ovarian Dynamics, Hormonal Profile and Fertility

<div>Background: Understanding of ovarian follicular dynamics and endocrine regulation is essential to design and use interventions to optimize reproductive efficiency. Bos indicus and Bos taurus cows have some differences in their follicular dynamics and ovarian steroidal hormones. The present study was planned to understand follicular dynamics vis-a-vis ovarian steroids profiles in Sahiwal cattle. 
 
Methods: The study was conducted in normal cyclic, pluriparous, non-lactating Sahiwal cows (n=7). Trans-rectal ultrasonography was performed to record the location, size, number of follicles and size of corpus luteum (CL) from the beginning, till the end of experiment. The dataset was used to characterize the follicular wave emergence, growth, regression, time of selection and ovulation of the dominant follicle in each cow.&nbsp; 
 
Result: Three Sahiwal cows showed two wave and four cows showed three wave estrous cycles with mean interovulatory length of 20.33&plusmn;0.33 and 22.50&plusmn;0.28 days, respectively. No significant difference was recorded in the maximum diameter of corpus luteum, P4 and E2 plasma levels between 2-wave and 3-wave estrous cycles. The peak progesterone values of 6.00&plusmn;0.91 and 6.2&plusmn;1.2 ng/ml and peak estradiol values of 15.83&plusmn;0.60 and 14.31&plusmn;0.44 ng/ml were recorded in 2-wave and 3-wave estrous cycle, respectively. The results showed that Sahiwal cows had 2-wave and 3-wave estrous cycle and the 3-wave estrous cycle had comparatively longer inter-ovulatory period and smaller maximum diameter of second wave dominant follicle than 2-wave estrous cycle.</div>

Studies on Ovarian Follicular Dynamics and Steroid Profiles in Sahiwal Cattle

<div style="text-align: justify;">The study aims to examine the temporal changes in economics of chickpea (gram), moong bean (green gram) and urd bean (black gram) production in western State of India i.e. Rajasthan. Study was entirely based on secondary data collected from publication of Ministry of Agriculture, Govt. of India, New Delhi. The structural changes in cost of cultivation were analyzed by working out the difference in cost at two points of time (i.e. 2001-02 and 2013-14), along with relative share to total cost. Study revealed that the average cost of cultivation of chickpea, moong bean and urd bean increased from Rs.9,941.66/ha, Rs.5,954.74/ha and Rs.7,849.31/ha in 2001-02 to Rs. 24,093.71/ha, Rs.17,793.53/ha and Rs. 21,346.36/ha in 2013-14.The net income over total cost was highest for chickpea which is a major pulse crop of Rajasthan. During 2001-02, both moong bean and urd bean remained unprofitable over total cost. During 2013-14, chickpea and moong bean became profitable over total cost. The level of profit was highest for chickpea followed by moong bean. Urd bean still remained unprofitable over total cost.</div>

Temporal changes in economics of pulses and their comparative advantage in Rajasthan &nbsp;

Background: Buffalo milk production in India plays a significant role in the global dairy market, with a rich history deeply intertwined with the country&rsquo;s economy and culture. Over six decades, the dynamics of buffalo farming have been pivotal in shaping India&rsquo;s dairy landscape. 
 
Methods: This paper delves into the subject by analysing a comprehensive time series dataset spanning six decades. The focus lies on understanding the economic and cultural significance of buffalo farming, particularly in relation to milk production. Four forecasting models-ARIMA, SES, Seasonal Naive and ETS-are employed to discern temporal patterns in buffalo milk production. 
 
Result: The study reveals that the ARIMA and ETS models outperform SES and Seasonal Naive models in capturing and elucidating data behaviour. Their superior performance underscores their efficacy in predicting buffalo milk production trends accurately. These findings offer valuable insights for policymakers and stakeholders aiming to optimize buffalo milk production and foster long-term growth in India&rsquo;s dairy sector.

Temporal Trends and Future Projections: A Deep Dive into India&rsquo;s Buffalo Milk Production Through Time Series Modelling

<div>Background:&nbsp;Meghalaya soils are highly acidic and phosphorus and boron are poor in supply leading to poor crop productivity. Low availability of phosphorus in these soils is due to fixation of phosphorus by Fe and Al oxides. Deficiency of boron in acidic soils of Meghalaya is due to coarse texture and leaching. The current study was conducted to find out the interactive effect of phosphorus and boron on their temporal soil availability, number of nodules in black gram and their dry weight.&nbsp; &nbsp; 
 
Methods:&nbsp;A field experiment comprising of four levels of phosphorus i.e. 0, 25, 50 and 75 kg P2O5 ha-1 and four levels of boron i.e. 0, 0.5, 1.0, 1.5 kg B ha-1 was conducted during 2019 taking black gram cv. PU-31 as test crop. The treatments were laid out in split plot design with main plot as phosphorus and sub plot as boron with 16 different treatment combinations and replicated three times in humid sub tropical climate of Meghalaya with acid Inceptisol having pH 4.99, available phosphorus 13.68 kg ha-1 and available boron 0.054 ppm. 
 
Result: The result revealed that temporal soil availability of phosphorus and boron increased with increase in phosphorus and boron doses, whereas it declined with progressive time intervals. Further, number of nodules in black gram and their dry weight show decrease with increase in time. Both these parameters increased significantly with increasing phosphorus and boron doses up to highest level. The optimum levels were recorded with combined application of 50 kg P2O5&nbsp;ha-1 and 1.0 kg B ha-1 for number of nodules and 50 kg P2O5&nbsp;ha-1 and 0.5 kg B ha-1 for dry weight of nodules.</div>

Interactive Effect of Phosphorus and Boron on Their Temporal Soil Availability under Black Gram [Vigna mungo (L.) Hepper] Cultivation and Nodulation in Acid Inceptisol